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Numerical Analysis

Code: INF32151     Sigla: NA

Áreas Científicas
Classificação Área Científica
OFICIAL Matemática

Ocorrência: 2022/2023 - 2S

Ativa? Yes
Página Web: https://moodle.ips.pt/2223/course/view.php?id=1856
Unidade Responsável: Departamento de Matemática
Curso/CE Responsável: Informatics Engineering

Ciclos de Estudo/Cursos

Sigla Nº de Estudantes Plano de Estudos Anos Curriculares Créditos UCN Créditos ECTS Horas de Contacto Horas Totais
INF 353 Plano de Estudos 1 - 6 75 162

Docência - Responsabilidades

Docente Responsabilidade
Artur Miguel Capêllo Brito da Cruz

Docência - Horas

Theorethical and Practical : 3,00
Practical and Laboratory: 2,00
Type Docente Turmas Horas
Theorethical and Practical Totais 5 15,00
Carla Cristina Morbey Rodrigues 9,00
Artur Miguel Capêllo Brito da Cruz 6,00
Practical and Laboratory Totais 8 16,00
Ana Teresa Agostinho Barros dos Santos 10,00
Artur Miguel Capêllo Brito da Cruz 6,00

Língua de trabalho

Portuguese

Objetivos

The main objective of the Curricular Unit is to familiarize the student with computational methods that numerically approximate solutions of common questions in calculus. It is intended that the student learns various numerical methods, its application, its implementation on a computational tool and how to choose the most appropriate among them, considering the problem to be solved.

Learning objectives:



1- Represent real numbers in different exact and rounded numerical representation systems.

2- Analyze in R^n the error associated with approximate values, and its propagation.

3- Carry out operations with matrices and apply them in the formulation of linear problems and error analysis.

4- Determine the set of solutions of linear matrix equations, through the inverse substitution algorithm and the Gaussian elimination method.

5- Identify Doolittle and Cholesky LU decompositions of square matrices, interpreting and applying the results.

6- Apply iterative methods to solve linear equations (in particular the Jacobi and Gauss-Seidel methods) and non-linear ones (in particular the Newton-Raphson and secant methods), analyzing their convergence.

7- Apply interval methods of bisection and false position in solving nonlinear equations.

8- Apply Lagrange, Newton and Gregory-Newton polynomial interpolation formulas to obtain approximate values ​​or zeros of a function.

9- Apply different quadrature rules, simple and compound, to obtain approximate values ​​of an integra

Resultados de aprendizagem e competências

Showing knowledge in:
a. Origin, properties and propagation of errors

b. Operations with functions in several variables, through matrix calculus

c. Algorithms for solving Systems of Linear Equations

d. for solving nonlinear equations

e. for polynomial interpolation

f. for numerical integration

g. its implementation through programming

h. its numerical properties

Developing Skills in:
1. Algorithm evaluation and control of its effectiveness

2. Algorithm Developing and programming

3. Algorithm application in practical problems

4. Appropriate algorithm choice for each problem

5. Algorithm results interpretation

Acquisition of Competences in:
i) Information and Communication Technologies

ii) Personal Valorization

iii) Planning and Analysis

iv) Autonomy and Initiative

v) Analytical Reasoning

vi) Critical Reasoning

vii) Creative Thinking

viii) Decision Making

Modo de trabalho

Presencial

Pré-requisitos (conhecimentos prévios) e co-requisitos (conhecimentos simultâneos)

Integral and differential calculus with real functions in one real variável.

Programa

T1. NUMBER REPRESENTATION IN COMPUTER SYSTEMS AND ERRORS
1.1 Number representation in a computer system.

1.2 Errors in floating point arithmetic.

1.3 Error propagation.

T2. SYSTEMS OF LINEAR EQUATIONS
2.1 Introduction to Matrix Calculus

2.1.1 Notion of matrix, special matrices, algebraic operations with matrices and inverse matrix.

2.2 Direct methods

2.2.1 Gaussian elimination.

2.2.2 LU factorization: Doolittle and Cholesky decompositions

2.3 Iterative Methods

2.3.1 Jacobi and Gauss-Seidel Methods

T3. NONLINEAR EQUATIONS
3.1 Bissection and Regula Falsi methods.

3.2 Newton’s and Secant method.

3.3 Polynomial zeros.

3.4 Fixed Point methods.

T4. POLINOMIAL INTERPOLATION
4.1 Lagrange’s interpolation formula.

4.2 Newton interpolation with divided diferences.

4.3 Newton interpolation with finite diferences.

4.4 Inverse interpolation.

T5. NUMERICAL INTEGRATION
5.1 Rectangle rules. Trapezoidal and Simpson’s rule

5.2 Newton-Cotes rules.

Bibliografia Obrigatória

Vários; Apontamentos editados pelo Departamento de Matemática.

Bibliografia Complementar

César Fernández; Sebenta de Análise Numérica (Available in the Moodle platform)
Atkinson KE; An introduction to numerical analysis, John Wiley & sons, 1990. ISBN: 0471624896
Correia dos Santos, F.M.; Fundamentos de Análise Numérica, Sílabo, 2002. ISBN: 9789726182863
Kharab, A.; Guenther, R.B.; An introduction to Numerical Methods - A Matlab approach, CRC press, 2018. ISBN: 9781315107042
Pina, H.; Métodos Numéricos, McGraw-Hill, 2010. ISBN: 9789728298043
Quarteroni, A.M.; Saleri, F.E.; Cálculo científico com Matlab e Octave, Springer Science & Business Media, 2007. ISBN: 9788847007185
Rao, S.S.; Applied numerical methods for engineers and scientists, Pearson, 2002. ISBN: 9780130894809
Scheid, F.; Análise Numérica, McGraw-Hill, 2000. ISBN: 972-9241-19-8

Métodos de ensino e atividades de aprendizagem

Student’s oriented study is performed through:
• Theoretical-practical lessons: Exposition of contents, followed by exercise resolution 

• Practical-Laboratorial lessons: Exercise solving with the employment of numerical calculus tools with Matlab sintax.

• Continuous avaliation with the application of 2 minitests and one test, and/or avaliation by final exam.


The objectives can be summarized as the knowledge of different algorithms, its properties, and all issues related to programming numerical methods on a computer. Thus theoretical sessions should serve for the solid presentation of the fundamentals. The presentation of contents, properties and exemples in theoretical-practical lessons, combined with the experimentation with these tools through specific exercises and Matlab programming should lead to the achivement of this course’s goals.

Exercise solving in theoretical-practical hours should serve for the assimilation of these notions, and its applications in different practical cases. Practical sessions with Matlab/Octave will develop the required skills in programming of scientific algorithms

Different supporting materials are available for the autonomous study: lecture notes, solved exercises, Matlab codes, formularies, web links, books (distributed at the classroom, Moodle page or IPS library)

Palavras Chave

Physical sciences > Mathematics > Computational mathematics
Physical sciences > Mathematics > Algorithms
Physical sciences > Mathematics > Mathematical analysis > Functions

Tipo de avaliação

Distributed evaluation with final exam

Componentes de Avaliação

Designation Peso (%)
Teste 100,00
Total: 100,00

Componentes de Ocupação

Designation Tempo (Horas)
Estudo autónomo 87,00
Frequência das aulas 75,00
Total: 162,00

Obtenção de frequência

The student can choose either the assessment by tests or the assessment by exam:

Test evaluation
This assessment consists of performing 2 (two) tests.
The final CF grade for the subject will be calculated using the arithmetic average of the two tests rounded to units and the conditions for approval are:
If CF is greater than or equal to 17, the student must take an oral exam. The final grade is given by the arithmetic average (rounded to the units) of CF and the classification obtained in this test. If the student deso not attend the oral exam, the final classification will be 16 points;
If CF is greater than or equal to 10 and less than 17, the student is approved with a final grade of CF, provided that the classification in both tests has been equal to or greater than 7.0.

Exam evaluation
The assessment based on the performance of exams follows the usual rules, that is, students who choose not to perform test evaluation, or who, having opted for it, have not been approved, may attend the regular exam periods.
If E is the classification obtained in the exam (rounded to the units), if E is greater than or equal to 17, the student will have to take an oral exam, obtaining as a final grade the average of the classifications of the referred oral exam and the written exam . If the student does not attend the oral exam, the final classification will be 16 points;
If E (rounded to the units) is greater than or equal to 10 and less than 17, the student is approved with a final grade of E.

Fórmula de cálculo da classificação final

Test evaluation
If (T1 and T2>=7) and T1+T2<=32, then CF=(T1+T2)/2
If (T1 and T2>=7) and T1+T2>32, CF=(((T1+T2)/2)+OE)/2

Exam evaluation
If E<17, CF=E
If E>=17, CF=(E+OE)/2

Avaliação especial (TE, DA, ...)

Students that intend to apply for specific evaluation rules that are recognised within the IPS normatives, must communicate (no later than 14 days prior to the test) to any of the Teachers these circunstances. They shall present documentary evidence that these specific conditions and rules apply to their particular case.

In the case that this comunication is not stablished, all testing conditions that imply a planning by the evaluator may not apply due to lack of objective conditions.

Observações

Specific rules for written tests and exams:


• Students must fill in the incscription list to take part in any test or exam. This process will be open on the Moodle platform the week before the test.
• The student must bring the formatted exam sheets to any written evaluation process (one cover sheet and 4 additional A4 sheets)
•The presentation of ID is compulsory on all evaluation tests and exams.
• Calculating machines are authorized in tests and exams, as long as they comply with the rules declared in OficioCircular/S-DGE/2016/1798
• Using, handling or even carrying of nonauthorized electronic equipments, different from tha calculating machine, is prohibited during the tests/exams.
• Students can bring to the exams an A4 sheet handwritten by the student for the porpuse of bringing formulas, exercises etc.


Moodle's Link : https://moodle.ips.pt/2223/course/view.php?id=1856

Password: AN223


Tutorial support in the teaching period:

Prof.Artur Miguel Cruz (Responsable teacher of the UC)
5ª feira 9h00-12h00

Prof.ª Carla Rodrigues 
5ª feira 14h00-15h00
6ª feira 12h30-14h30

Prof.ª Ana Barros
3ª feira 10h00-11h30
6ª feita 10h30-12h00

Tutorial support in the exams period will be determined after the corresponding exams schedule is approved.
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